Everything in the book will have practical application for information security professionals. The entire purpose of data analysis and visualization is to gather feedback from the environment to make better and more informed technology decisions. Within information security that means identifying ways to prevent or detect breaches and then measuring the effectiveness in doing so, which is all wrapped up under "risk management." All of the examples will be directed at answering real-world questions. One of the key points is not just to analyze what is in front of us, but collect and analyze the data we need to answer the questions that will lead to better decisions and prevention of hacks and vulnerabilities.The book will present the core elements of analyzing I.T. system data and information security feedback by using 30 use cases and domain-specific data sets with a focus on practical "how-to." This hands-on approach will be covered in context and will not be limited to just the analysis, but all the supporting skills needed to learn from our data. Data analysis from start to finish: from the data collection and preparation through the data storage and management fundamentals then into the analysis and finally data visualization and communication techniques all in the context of security.Use cases will include: Discovering anomalous firewall trafficHow to acquire and prepare security dataCreating a repeatable data analysis toolkit and workflowWhitehat stats reportSecurity event correlationVulnerability countsUsing inferential stats to detect malware outbreaksVisualizing system logsMapping BotnetsUsing NLP and Data Loss PreventionPredicting rogue behaviorHow to perform predictive analytics

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